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Podcast with Michelle Tenzyk: Uber, Lyft and Self-Driving Cars, Facebook Diversity, Amazon’s AI & Robotics, Gig Economy, Future of Work

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Terry Tateossian (00:03):

Today we have Michelle Tenzyk who is the CEO and founder of East 10th group and the strategic advisor and executive coach to CEOs. Michelle has over 25 years experience in business as a strategic advisor and she helps drive actionable people solutions and provides practical insights on business strategy to senior leaders. Michelle, welcome.

Michelle Tenzyk (01:07):

Thank you Terry. Loved being here today. Thank you.

Terry Tateossian (01:09):

Absolutely. Likewise, we really appreciate you taking the time and speaking to us about your expertise. So let’s talk a bit about your background and how you got started in HR management and HR systems.

Michelle Tenzyk (01:24):

Sure. I have my MBA and HR systems and management, and at the time, it was a long time ago, getting a degree in HR systems was not popular. That was not yet known about in a more mainstream way. And getting that degree when I did, first of all, the school I went to was really the only school in the country who had that degree. And it made me a ver a choice candidate when I went for interviews because I was bringing a skill set to bear in the world of HR that not many other people graduating with an MBA hat. So I think back on that now and I think about today and I go, okay, so today you would look for similar backgrounds and people analytics, AI and automation in a degree that fundamentally has HR as its undercurrent. And that to me is the most attractive candidate.

Terry Tateossian (02:27):

What are HR systems?

Michelle Tenzyk (02:29):

Yeah, so HR systems at the time was being able to create a system where you were housed all the employee data in a way that you could access it easily for analytical purposes and for processes. So how do you process analytics around your head count for an organization? Where do you keep all the fields and data about an employee name, address, age, all the things that you need as an employer about your employee in order to pay them, to service them, to give them salary increases and to manage them well and also put them in the right places in your company.

Terry Tateossian (03:14):

Very interesting. What would you say are some of the challenges right now that um, HR, the HR industry as a whole is facing today?

Michelle Tenzyk (03:24):

Yeah, I just read a study coming out of IBM and what I found so fascinating about this Terry, is they talked about the need for HR professional themselves to get updated on and re skilled on automation, AI and systems. Somewhere along the way, HR, I don’t know if we do railed or we sort of went off the ranch a bit, but we were not staying as current with technology. HR traditionally can be a very administrative, very task heavy field and so the time it takes to implement more efficient systems, sometimes it’s just difficult. But today the first really stopped for most organizations is to rescale and Uplevel your HR team so that we can then implement the right solutions for your company on this whole new future of work.

Terry Tateossian (04:23):

Right? I mean, nowadays with all the different technology that’s coming out that could potentially automate a lot of the data entry and administrative tasks that HR professionals traditionally have been tasked to do now technically frees them to do a lot more.

Michelle Tenzyk (04:43):

That’s right. So what it frees them to do is more complex decision making and really input on strategy. The automation of data has been around for awhile in HR. So you know, in the early, as I mentioned, the systems, a company called PeopleSoft at the time, which is now Workday eventually became Workday or I think I might’ve had that wrong, but, uh, the founder of PeopleSoft also founded Workday. So those kinds of systems have been in and around the HR world for a long time. Even big data analytics has been around now for quite some time in the HR world and automating an employee self service. So I joined a company and my ability to access my paycheck, change my tax deductions and so forth is online. I have, I have a service center I go to. However the, where the push now is happening is it’s being pushed in recruiting, onboarding, predictive analytics about where I’m going to need the talent when and even quality of talent. So it’s now in its, in its next phase in iteration to take away any of the manual task and completely automate that. So it frees me up as an HR professional to really be involved in setting strategy for the organization in a much more meaningful way.

Terry Tateossian (06:10):

Very interesting. Tell me about how big data, um, I’m always fascinated with that subject because big data usually doesn’t give you, uh, the type of insight or you know, you can kind of manipulate the insight to give you what you want it to give you. But um, how does that play a role in decision making in HR in general? What does that mean?

Michelle Tenzyk (06:32):

Yeah, so a great example is I knew the second in charge of HR for Halbert and global VP of human resources. And when you think about Halliburton and with the multitude of oil rigs around the world and the production of the oil and the labor that’s needed to be on the oil rig, depending on how oil is coming through or not, that’s where big data and analytics comes in for human resources, right? So how do I determine and predict who I need win on the rigs in order to maximize the production effort at a particular point in time? So to me that, I mean that’s in a large sense, but yet it’s quite powerful when you think about it, right? So that’s, that’s not only big data analytics, but it’s also using predictive analytics so that I understand how to manage my labor market well as I need to, to meet demand as I need to around the world.

Terry Tateossian (07:45):

And that’s where I guess, um, artificial intelligence, machine learning and predictive modeling is now kind of piggybacking on top of big data and beginning to create a lot more, uh, interesting ways of using the data to,

Michelle Tenzyk (08:04):

and I agree with that. I completely agree. Because when I think about big data, I think for a while it was big data for the sense of, Oh, I have all this data, I’m going to mine it, I’m going to look at it. And then what? Right. And then the, and then it was and then what? So do I then have to go back and have the human intervention, right to understand the data and now no, there are now systems, mainly AI that will interpret that data for me. And then my role is, okay now take the action based on what the data has told me and been interpreted to tell me. So it’s, it’s really quite an nuance but dynamic change to big data. Yes.

Terry Tateossian (08:51):

And one of the things I think that are very controversial, especially in the HR industry when it comes to AI is I think you and I talked about this before, is the type of algorithms that are coded to interpret the data, have their own biases built into them because of the nature of what AI actually is. And what it does is it consumes the information based on the input that it’s receiving. And then based on the rules that have been programmed in its core, it spits out information back. I mean this is a very interesting subject matter I think in general because there is really no answer and no solution. We don’t know yet.

Michelle Tenzyk (09:33):

I don’t know. Cause we were talking about is, and something that has been highlighted to me in talking about AI is, okay, so in order for AI to actually work, at some point humans are doing something to either input the data, integrate the data. So there is a human intervention at some point with AI and who’s around that table, who’s actually influencing that integration to make the AI solution work. And if I’m looking at technology today in the STEM areas, we still have an underrepresentation of a full diverse workforce, right? That’s supporting even the front end of AI. And so then you ask yourself questions, then is there inherent bias built in on the front end? Almost what they call is unconscious bias, not even, not even knowing, but yet that’s built in. And so therefore the results from AI have a bias in them, right?

Michelle Tenzyk (10:48):

So there’s a colleague of mine who now has founded her own organization company coming out of the AI space on the legal components and ethical components, right, of AI and what’s going to happen. And we talked about just this case where it’s been proven that certain ways of of AI working well gets influenced on that front end and what might be the bias. And I think you were the one who told me example, which I still think is hilarious on the Twitter feed and Microsoft and the bot that was unleashed on Twitter, right? And then all of a sudden based on interactions with whomever was reacting to it, people wise, it started spitting out tweets that might’ve been seen as very inappropriate because it was learning, right? Cause it was learning as it went, but being influenced by the human intervention and therefore comes out with what is extremely biased,

Terry Tateossian (11:52):

extremely problematic for Microsoft. Yes, exactly. I mean it, it, it was kind of launched this, this innocent, happy, cute little bot who was not programmed to expect this type of behavior. And of course it didn’t have any ways to filter it out. So the filtration system within the intelligence that was created for Twitter was kind of faulty in my opinion. I think that’s where it flopped.

Michelle Tenzyk (12:21):

And what, what really comes to mind when I hear you say that is I think about, you know, what I do for a living today, what my company does for a living today, which is, you know, supporting leaders and their organizations to reach their full potential and realize their strategic plans. The leaders today, cause I’m actually doing a vision session with one of the CEOs and companies we partner with tomorrow, their future is dependent in that organization on AI and automation. It just will be. And so when I think about this leader’s ability to articulate a vision for the future, right? We think about visions, big idea, big goal maybe feels not reachable. You want to put something big out there. He’s got to be influenced by what’s happening in the automation world for his organization and his clients that they service. And that takes an incredible amount of emotional intelligence because you really have to be sensitive, knowledgeable. You have to have the wherewithal to go, okay, I may not completely understand what’s coming down the pike, what’s all of this is going to mean in 10 to 20 years. But I’ve got to take that into consideration when set setting a vision and that means you’re going to have a high level of emotional intelligence. So you need to have that sensitivity and wherewithal about what will my workforce potentially look like, come 10 years when my vision may be realized.

Terry Tateossian (14:02):

Absolutely. Which is something that Amazon is grabbing a lot of headlines right now where they just announced that by I believe 2025 they’re going to retrain, re-skill, or upskill their workforce. Half of its workforce, I believe were a third of its workforce. I think it’s a hundred thousand. Yeah, some a hundred thousand like that’s crazy. And other companies have joined this movement like 18 T and Walmart, um, you know, WMT and so forth. JP Morgan chase, Accenture, and I mean, I think it’s very interesting that they’re seeing it. They know what’s happened.

Michelle Tenzyk (14:45):

Well, they’re getting ahead of it, right? It’s no different than Amazon, JP Morgan and Berkshire Hathaway coming together to form Haven and start addressing the healthcare issues in their organization for over a million employees. Right. And addressing what that needs to look like as opposed to waiting for government to solve that issue. So there is no doubt that in that frame they are using AI and automation to solve for that healthcare need for their million plus employees. And so why wouldn’t they do the same for there for these employees in terms of upskilling and training them to best service the consumer population that they need to reach in the future. And why lose your workforce, right? Because that skill set is not available anywhere for the most part. Right? Or if it is available, it’s available in so small quantities. It’s not enough to remain competitive and be the leader in the marketplace.

Michelle Tenzyk (15:49):

So somewhere employee employers have to make the investment in their own people that they have who are willing and able. And that’s, you know, typical. So there’s going to be employees who put their hands up. There’s going to be employees who are sort of step back and go, no, not yet. I don’t think I can do that. And then the employees who go, yeah, not for me, those employees will lose out. They will lose employment because it’s going to be much harder to find something that they can do if they don’t get upskilled. What would you recommend that people do to on their own right now to keep their skills not just relevant but you know, future thinking or future forward to be able to meet the demand of the workforce in the next 10 years? Yeah, there’s so much available right now online, right?

Michelle Tenzyk (16:38):

Um, in the HR field, there is a, uh, uh, PR course that came out last, I don’t remember if it was the summer early fall, uh, put out by the, uh, organization called the future of work. And it was on AI for HR. I signed up, I took it, it was a five week course online using combined AI as well as automation, a great learning platform. So I was exposed to new tools and new ways of doing work. And it gave me a deep dive into lots of different applications and AI supported solutions within HR. That is what I recommend is just get yourself up to speed. Don’t be afraid of reading, learning and looking. There is tons of free courses out there. In fact, Google has released, they were upleveling their employees for AI and their course on, I think, I don’t know if it’s called Google for AI, so I don’t want to be quoted on that, but it’s something within that. You can Google it, you can Google it and you’ll find it and it’s, and it’s free. It’s in the public domain and free, so why not get yourself exposed and the more exposure you have, the less fear you have then the more than you feel it’s you’re capable and I can do it or if I’m not going to do it, I’ll find a partner who can do it.

Terry Tateossian (18:12):

Right. Exactly. Amazon, which is one of my favorite use cases to always just kind of look at what they’re doing going forward. You can gauge a lot about just technology in general and their consumer centered approach to the business and how they do things is actually replacing a lot of their workforce and I think this is part of the reason why they’re retraining and reskilling and upskilling. They’re replacing a lot of their workforce with robotics technology where they’re going out and they’re picking and packing and delivering the orders to a human being who then takes care of the final stages. And this is something not even that recent, I mean this is something that’s kind of becoming the norm, I believe in most of the, the larger retail chains that are competing with Walmart, but I thought that was really fascinating that Amazon now is able to compete with one of the biggest retail giants of the world. Walmart and Walmart is becoming somewhat concerned about Amazon

Michelle Tenzyk (19:31):

finally. Well, I think they’ve been concerned about Amazon. I think everybody is. Amazon is pretty much taking over the world. When I think about that, a few, a couple of years ago I was in the Midwest and for a conference and we were at a particular company. That’s a manufacturing company and we got to see the plant that was extraordinarily antiquated. I mean, you could just feel it. The building itself, the machinery, you know, they were priding themselves. Well this was the original machine and that’s what, and I just went, Hmm, interesting. We then went the next day to see the F-150 plant for Ford that was being run by robotics. Now there were people on the assembly line, right? Managing certain handoffs of the robotics. But it was bright. It was airy, it was modern. There were um, people on the floor. But again, the robotics were putting on the door, putting on the hood, putting on the handle, and then it’s moving to the next section.

Michelle Tenzyk (20:42):

Now what has to happen is why people are needed is to ensure that it moves the next section. And the work was good, right? So you’re doing a quick quality control check at that moment. So robotics has been around, as you said, this is nothing new. And it’s a matter of where do people get plugged into the robotics, where the human touch and human sensibility is still required to ensure that the output is what you want it today. And that’s, yeah, and that’s, and that’s what Amazon is contending with now is yes, robotics, but are we sure that it was done in a quality way and there’s going to be a certain human intervention that’s required for that. And let’s not forget though, this is where we talked about upskilling. So if you think about those kinds of robotics now you need more people who understand their robotics, right? And how does that work in order to intervene in the machine that might be doing that. And that’s an upskilling, no different than the industrial age where you know, the automation lines came into play and you needed to have people who understood how that automation line worked.

Terry Tateossian (21:55):

Yeah, I hear all the time that, Oh, AI and robotics, they’re just going to replace all jobs and we won’t have any jobs. To me it doesn’t make sense because I feel like we’ve gone through quite a number of industrial revolutions over just even the short period of time that I’ve been alive, forget about in the last 150 years. And this is just another example of that. This is just another way that we’re going to shift the way that we do work. And that’s been happening for quite a while now. You know, same thing with, um, you know, when farming equipment change, we no longer needed hard manual labor to do those things. And what happened to all the farmers while they became machine operators? They started working in the factories. And what did that do? Well, we started having cars instead of carriages. Well, what did having cars do all well we can now travel much faster again, more, you know, everything just kind of contributes to getting more work done, being more efficient.

Terry Tateossian (22:57):

Same thing with the computer all, you know, everybody saw when the computer came out that it’s going to just put everybody out of work. Well, no, it actually put, put a lot more people into work. So every time I hear this fear based argument for people telling me about, Oh, AI is just going to destroy everything, it’s going to, you know, put us all, you know, have us all be homeless and have no jobs. We won’t be able to do anything. I say, why? Why is that your argument, you know, where do you get the sense that that’s what’s going to happen?

Michelle Tenzyk (23:29):

I think it’s, um, I was just thinking, I was laughing to myself when I was going for my graduate degree. We went to a computer lab to sign on to maybe the one or a few computers that we had to do the work, right? And today, you know, we all have one, we might have multiple laptops, right? And that’s just the way it works. And it wasn’t less employment needed. It was more employment needed because of the advent of how much technology brings to life in general. It’s just different work. There’s a very sophisticated leading edge. Chinese gentlemen, I don’t remember his name, but he talked about that. Yes. In the next decade, 40% of the current workforce will be completely changed. So meaning either you will lose your job or you will have an upskilled and your job will have changed and what you do is going to change, but it is going to be that massive.

Michelle Tenzyk (24:29):

So no different than I needed to come out of the computer lab and get used to using a laptop or a desktop at the time and that we all had computers and learn all those programs. It’s no different today and so there is a little bit of a jump on board or you will get left behind. And so there’s, that’s human nature. Some of us will grab onto it, others will be a little more resistant, but it’s coming and it’s coming fast and that’s just that I think is causing more overwhelmed because of the speed now of these changes. People feel overwhelmed by that and that’s where employers have a lot of responsibility and lots of opportunity to really dynamically help their workforce change. Otherwise they as an organization will get left behind. I mean, look at how many companies are no longer in existence. There’s a number of them on my resume that are not in existence for lots of different reasons. So that’s where we’re headed now. And I always, I’m wondering, will Walmart exist in the foreseen future or will they have to so dynamically change in order to remain competitive with an Amazon and offer a different way of buying retail?

Terry Tateossian (25:39):

Absolutely. Which industries do you think will be most disrupted at the, at the very beginning and reach out?

Michelle Tenzyk (25:46):

Yeah, without a doubt. Yeah. I just walked past, I, I was coming over here and I was walking past the Brook brothers store and I started with them. Does anybody shop in Brook brothers anymore? But they now have a full cafe coffee cafe in there to create more of an experience for their shoppers. Right. So, Hey, if I come in here for coffee, maybe I’ll also look around. And so it really is about that retail experience now, which we’re seeing the change happening. So it’s no longer just going into retail stores and having racks of clothing or shoes. It’s about how do I create an experience for someone to want to come in to be in this store and to do something while I’m in the store. But retail by far in my opinion, is changing the most and then automotive. So that would be second is that automotive is going to change massively with the advent of self driving cars, flying cars that’s coming and healthcare. If you think about healthcare right now, you know one part that is already you can see changing depending on where you decide to go for your medical services, is the ability for a multitude of doctors to get my records, to see my record in one place so that they all know what’s going on with me. So healthcare is massive and it needs to be because it’s complex, but that is going automotive and retail and I would put those three on very similar trajectories of massive change.

Terry Tateossian (27:20):

Yeah, absolutely. I was reading an article like, I think it was in Forbes talking about how specifically the grocery store industry has just really changed and evolved because people don’t want to go to the grocery store anymore. Apparently. And the way that a large chains are changing that and a lot of times the grocery stores are in the store and in the forefront of innovation because they have to, they’re changing it into experiences. So you’ll walk into a whole foods and it’s a cafe or something,

Michelle Tenzyk (27:52):

French restaurants, it’s to get you in there

Terry Tateossian (27:55):

old time butcher and you know, everything is kind of virtualized where you get to experience the foods in addition to the environment. And that apparently brings people in a lot more and it has them buying.

Michelle Tenzyk (28:09):

Yeah, it does. Well it’s funny, I don’t live in the city and I live outside the city alone North of Manhattan and I go to what I would consider a fairly traditional grocery store. But I do self shopping. So I, you know, as soon as they put that in, I got my own little thing to get my groceries to, you know, get scanned the pricing myself. So then it’s a very easy, and I bring my own bags. Everything’s bad. I don’t have to deal with the checkout counter. But the other day I was in that store a couple of weeks ago and I heard someone say, may I help you? And it was a robot wandering around the store checking if I needed anything and was a little disturbing. But I was like, Oh okay. So now we have robots. Right. Helping to make sure I’m okay in the store.

Michelle Tenzyk (28:58):

Did you tell him? I think I was so shocked that I had a robot talking to me in the grocery store. I walk the other way but next time I will interact. Cause I’m fascinated now that I’m a little over my shock. Like what are they going to help me with telling me now. So what does it look like? It looks like a segue way in a way. I mean that’s what it made me think of. Although it was tall and had some kind of smiling wishful thinking, I would have had them do all my shopping then, um, with a smile on the face. It was just really odd. Yeah. Two dots. Yeah. Yeah. Yeah. But again, I looked so quickly cause it was so to me

Terry Tateossian (29:45):

I had to look away and just,

Michelle Tenzyk (29:48):

but next time I will interact. Yes. Right. What grocery store was that a stop and shop. Yeah. So check that out. Right. But then you know, you have all the home delivery rights. So that’s changed and you know, yes. Has it now reduce the need for cashiers in a grocery store? Absolutely. So people who are skilled at being at a grocery line as their job or packing groceries, those people are losing their jobs. That’s real. I mean, that’s not not happening. And then what will people in those kinds of roles do? I don’t really have an answer for that. I don’t know. Um, they, it, there’s, at some point, you know, even when I think about stop and shop and the, the woman in this particular store that stacks and puts in the vegetables, the fresh vegetables, well, in a number of years that will go away. There will be a robot putting those vegetables in their places and you won’t need, because it will be quicker, faster. You won’t need the human doing that kind of work. And so what will that person do? I don’t know. I don’t know if they get re-skilled or able to become something else or do they lose their jobs. But just like in the industrial ages of, you know, initial automation, there were people that lost their jobs and it was really challenging for them.

Terry Tateossian (31:13):

Right? They even have now technology where you can just simply walk out of the threshold of store and it automatically scans the items and it charges your card. So you don’t even need a cashier at that point there. A challenge, however, is to make sure that they charged the right people for the right things. So I guess the geo locator or scanner or the sensor or the IOT device, I’m sure it has to be accurate most of the time. Or they’ll have a massive consumer issue on their hands. But that’s coming

Michelle Tenzyk (31:47):

well. And if you think about, you know, toll roads, right? So we used to go through the toll booth, you know, we’d have someone there that we’d get a ticket from or we’d give them money as we were driving along. Now they have all the over there taking out all the toll booths and it’s just the overhead, you know, cameras, technology, et cetera, that are picking up a signal from your car, whether or not you have the pass or not. Right? Many of us have heard of easy pass. You’re going to get somehow mailed at home. It’s working. The technology is working like all the bridges in the New York city area, all the toll booths are out and it’s all overhead and it makes life so much easier and faster. So all of those individuals, what are they doing today? I don’t know what they’re doing right, but somehow they’re working somewhere. They’re finding jobs elsewhere or they’re getting skilled up.

Terry Tateossian (32:39):

Right. Hold that thought.

Terry Tateossian (32:41):

Let’s take a quick break and thank our sponsors. The production of the amplified podcast has been brought to you by social fixed media. Social fixed is a transformational growth hacker agency focused on emerging technology platforms, video and podcast production, content marketing and overall startup strategy. Social fixed has helped over 300 clients generate millions of dollars in revenue fund raising and a profit if you’d like help launching or growing your business visit [inaudible] dot com. I don’t know how

Terry Tateossian (33:17):

close this is to actually coming to fruition, but I was reading, um, about technology that’s going to change the road material itself where roads will be able to self-direct themselves and change to avoid traffic and fix themselves and pass some type of plasma or whatever they’re using to make the roads. So, you know, even construction is I think one of the industries that will be very significantly impacted because right now everything is done manually where the land surveillance, the um, you know, actually going through and looking at the land in three D and figuring out, you know, or x-raying it or whatever it is that they do to see what’s underneath. You know, all of that is going to be I think significantly changed and it’s already happening even in the manual, especially in the manual labor industries.

Michelle Tenzyk (34:19):

Well, I think, I think what’s important is, and this is where I think the human resource profession has such an opportunity is you know, I’m even getting overwhelmed listening to this. Like what I didn’t hear about the road thing. I mean that’s new. It’s almost, you know, every day, every other day, every week, all depending on what you’re reading, listening to, Googling, looking at that, you’re going to hear something new in this world of future of work as we call it, the opportunity for HR though in companies is to help bring their leaders and their teams along with this and not make it something to be afraid of or overwhelmed. And by embedding this in the way the company is operating, right? Making sure that whether there is ongoing podcasts or there are leaders communicating in a particular way or easy access to information and giving employees actually time to look at this kind of information is all within the HR responsibility. And so HR can have such an absolute critical role going forward in how companies are orchestrating their understanding of these changes. Taking on these changes and letting people feel okay with them, that it’s not something to be as overwhelmed with, but it’s going to be okay and this is what you do about it. And by exposing people to it, so HR is key and all of that.

Terry Tateossian (35:46):

What do you feel right now just being in the HR forefront, what is being done right now to, uh, help people get re-skilled up-skilled or lead CEOs or, um, lead CMOs, CTOs and so forth into this coming shift that’s happening?

Michelle Tenzyk (36:05):

Yeah, so I think what’s interesting about that is the kinds of companies that we work with are primarily in what we define as the middle market. So usually about 50 million revenue upward of a billion. So we’re not in the large, we’re not in the Facebooks, we’re not in the Amazons and so forth. And so a lot of our clients have their, there’s limited dollars in terms of what they can spend and make the investment in. And so what my reaction has been is it they feel to me a little behind. And what I mean by that is if you take a very technology savvy forward thinking organization, and I think I mentioned this company to you awhile ago, a n***a who is in the big data analytics space and more than that, I’m a little behind probably in what they’ve done up to now. So a company like an enigma that’s about 125 employees, they are putting in squads to uh, how they do cross functional work in the organization.

Michelle Tenzyk (37:08):

So I’m on a squad for 90 day attached to a project with a number of the other people in the company and then I switch out after 90 days and move on to another role. So HR to me is helping because they’re helping to orchestrate that and they’re helping to put in mechanisms for the managers to evaluate the work and to provide feedback in a meaningful real time way larger middle market firms. However, there are some fundamental challenges with the amount of resources they have to be as agile as they need to be. And that’s where I’m going to go back to. It is incumbent upon the leadership team to not shy away from all things AI and automation and to literally do deep dives into it so that they can position their employees and their people for what is already here and then ensure that they remain competitive. So that might mean making some distinct differences and investments in order to have that competitive edge going forward. And those are tough decisions. Those aren’t easy decisions to make, but they’re going to be necessary to make.

Terry Tateossian (38:18):

How would you recommend the middle market CEO of, you know, let’s say a fortune 1000 company? What would be the steps that they should take? Or how should they even begin?

Michelle Tenzyk (38:30):

Yeah, so I think a couple of ways. I think one to, uh, of the CEO’s we work with, uh, just attended a disruption conference at MIT. Fantastic. Just getting exposed to what’s going on and especially outside what might be your own industry. So getting influenced by other industries and other CEOs in terms of what they’re being challenged with. Um, another CEO we work with in the industrial space. I encourage them to go to the ideas festival and Aspen in June. Why? Because there is broader global thinking that’s happening there. There is, it’s intersperse with economics and the marketplace and the worldview which then brings you back to your home base, influenced by other ideas and thoughts and you can start formulating what your future dynamically really needs to look like. The other thing that just occurred to me today that I would recommend to a CEO in that position is also to be thinking about if we can’t move our environment from within, what acquisition might I have to look at to help drive this for the future? So go out and find potentially a very technology forward, smaller organization that you can then tack onto your own, which will propel that advancement.

Terry Tateossian (40:02):

Very smart. Yeah, a lot. A lot of tech companies are getting scooped up. A lot of creative companies now are getting scooped up because I feel that the creative industry is going to be one of the last ones disrupted in terms of problem solving and creative problem solving and so forth. But it’s going to be also one of the industries that will be the highest in demand. Creative aspects.

Michelle Tenzyk (40:31):

Love that. You talked about that because when I’m reading now about what is the human skillset that’s going to be most needed is complex decision making, strategic thinking and creativity. Because even, you know my suggesting that maybe a bit of a state organization that still has a place in the world that still has customers still has a particular market share. Thinking about how do I add on a technology company into the mix? You need to be creative to think that through and you also need to be a risk taker, right? You’re going to, especially if you’re a publicly traded, you’ve got to convince your board, you know, your constituents, your shareholders and so forth, that that’s a good investment. But yet that’s what the future is and that takes a tremendous amount of creativity and forethought. So you’re right, Terry, you’re a hundred percent right. And I’ve just seen that in actually some research.

Terry Tateossian (41:31):

Yeah. And, and you know, a lot of people that are creative, I feel like erroneous sleeves believe that they’re not meant for the technical industry, but that’s where the diversity of algorithms come in. That’s where the creative problem solving in the enhancement of the AI, it needs that. The way that I kind of visualize it is that the stage that we’re in right now with AI, it’s, it’s a little tiny infant, a little baby. I mean, that’s what we have on our hands and we need to train this intelligence or this, you know, this awareness into seeing what the world is like and maybe being able to make those decisions. But we’re nowhere near that.

Michelle Tenzyk (42:13):

No, no. But it’s coming fast. Right? So if we have this conversation three years from now, there will already be substantial changes to what we’d be talking about. Yes. That’s just the facts. You know, in a year or two years, I’m not sure. But by the three-year point, yeah. In fact, the way we’re even recording this podcast might be very different than thinking it. That’s right. That’s right. That’s right. Well it’s interest. I think there’s some commercials now. Yes. I’m still a TV watcher. There’s some commercials on TV that are using, you know, what the future might look like. Right. Watching a TV show through glasses and being able to just fast forward quickly to get to the spot that I want to get to. Um, and not needing to be in front of, you know, nevermind even streaming that. I’m just able to project that wherever I’m standing. So is it going to get here? Sure. It is. I don’t think we ever thought flying cars were going to get here, but they are. They’re already here. They’re already testing them.

Terry Tateossian (43:15):

Yes, exactly. If anybody wants to see a real flying car. See yes,

Michelle Tenzyk (43:20):

that’s right. 2020 CES, no doubt about it.

Terry Tateossian (43:22):

Talking about the technology that’s coming, holography is one of the most fascinating subjects, I think in general. One because I think most people like me assume that the phone, our phone that I’m attached to that you wouldn’t recognize me if I put it down. We’ll be around for awhile, but in actuality there are companies right now working to actually put that out of business and have the phone be a hologram that’s displayed on any surface and the technology behind it could be bio somehow triggered.

Michelle Tenzyk (44:02):

I think it’s hard for any of us to imagine that our smartphones, which we all are now attached to and are, you know you see one year and two year olds using them that they are going to go by the wayside. Our smartphones are not going to exist. My projection on that is an only, this is from watching again, this gentleman from China who’s a leader in this space and I believe he said, I think he said it was in five years I might be misquoting him, but our smartphones are going

Terry Tateossian (44:32):

away. They’re not. And that’s sort of like, what are you kidding me? How will I exist without that? Well there’ll be something else that will take its place. Exactly. I mean the phones replaced the computers. That’s right. And now there’s something coming that’s replacing the phone. That’s right. And that that will be happening much sooner than I’m imagined. And then I don’t know what we’re going to do. We’re all going to be part of the gig economy. Right?

Michelle Tenzyk (44:57):

Yeah. You know, I think that that’s an interesting part of the conversation, right? Because the gig economy is now, right? Where many companies are utilizing a variety of ways to get at what they need to produce the work. So it’s not unheard of that a team that I might be collaborating with has people who are full time on the team who are getting their pay from that employer on a full time basis. But it’s going to be interspersed with people working virtually, people working from around the globe. There’s going to be add on skill sets that we don’t have internally in the company. And you’re just seeing that more people. And, and when you think about it, people are freer to work from anywhere. And that has promoted the gig economy. And if you go back to the example I used on a n***a, right, so if they’re putting together squads which says, okay, I need to be on a project for 90 days and then I’m going to move on to another project because that work, the work that I needed to do is done and yet it’s exciting for me and motivating for me because I get to move on to something else that supports the gig economy that allows someone who wants to quote unquote freelance or not be attached to anyone company move around quite easily.

Michelle Tenzyk (46:18):

I think it was interesting. I met a group of young graduates a couple of years ago coming out, I want to say they were coming out of the new school. It was either Bruker, the new school. They were forming already their own conglomerate of different skill sets as opposed to joining up with a company. So they had found that they liked each other in the school environment. They had different technological skills for the most part, graphic design, communicate all different pieces and they were joining together to become this offering. Right. Is here, we’re going to have all these different skill sets. I thought it was the smartest thing ever. Like, why not? Right? I don’t have to get attached to a company. I can just share my skills and get hired out and they’ll get hired. I have no doubt that they’re probably doing well today. Probably tripped up a little bit, but I’m sure they’re doing well

Terry Tateossian (47:10):

as any startup trips up. That’s right. Yeah, exactly. Exactly. Something that’s been on the horizon, I think with more and more intensity lately is um, a couple of companies, obviously the big tech giants, uh, Amazon, Facebook, Google, et cetera. But Uber and Lyft have also begun experimenting pretty heavily with autonomous driving cars. And it feels like, you know, Uber was such an innovative, disruptive type of company where it didn’t own anything. It didn’t employ anyone. It had no assets. It just had this app, but it had the power to put millions of people to work. Now it also has the power to put millions of people out of work. That’s right. And I feel like a lot of people are very stressed out, very nervous about what’s going to happen. Specifically in, in the driver.

Michelle Tenzyk (48:17):

Yeah. Industry. Listen, I mean that, that’s you think about now flying into New York and LaGuardia or JFK and whatever and we’re all out there and getting our cars. There are some people who still are in the taxi line, but that certainly has gone down. You know, taxi medallions in the New York area used to be over a million dollars. Now I don’t even know what the price is. I’m going to say maybe a hundred thousand at most. So, and you’re putting taxi cabs out of work. I mean they don’t have jobs. And what are those folks doing? I can’t tell you what they’re doing. Um, I haven’t asked a taxi driver as of late, you know, what, what worlds are you going for work if this is no longer your job. And certainly now if the next disruption of this industry is they will be self-driving cars.

Michelle Tenzyk (49:06):

So I won’t need actually a driver in it, then what are those workers going to do? Just as all of a sudden there were plenty of workers to drive Uber’s, they came from somewhere. Right. There will be the next thing that those drivers can do. I mean that’s, I have to be hopeful on that cause otherwise yeah. Will be a lot. Same with truck drivers, right? I mean there’s a, there is now a need for truck drivers. We don’t have enough truck drivers. We just don’t, people are not getting into that field, but yet you sort of say to yourself, okay, well but are we going to need truck drivers in the foreseen future? Regardless of the challenge right now is there’s not enough of them.

Terry Tateossian (49:46):

Right. There’s a lot of professions that are I think lacking.

Michelle Tenzyk (49:49):

Yeah. The trades, the trades, the trades are definitely lacking people coming into that because the folks in grammar school and high school are necessarily thinking about the trade as a way to make a living. Yet it can be an excellent way to make a living, but they’re not thinking about that. Cause if you think about a tall building going up in any big city for the most part, regardless of cranes and other things, the likelihood of not needing human beings to help put that building up. I think for the foreseen future, human beings will need to help put that building up. And so those trays be required. And so perhaps with, I dunno, I’m just thinking this off the top of my head perhaps now with all this advent of automation and people who may not be able to be upskilled in that side of the equation, they’ll end up going over to the trade side possibly. I don’t know. Cause that could be a possible place for them to get employment at work.

Terry Tateossian (50:48):

Yeah. And then you know on one side you have the talent acquisition, panic and on the other side you have the unemployment panic. Which point of view is actually the accurate depiction of what’s happening because I am one and I feel like we can’t get enough people to come through that have the skill set that’s needed. And on the other side, people are saying that, you know, they’re going to be replaced.

Michelle Tenzyk (51:16):

Yeah. So on the talent acquisition side, and this is only my opinion, I’m not going to be able to quote facts and figures to back this up. Companies, it feels like the ones that I’m exposed to in the last few years, even with the tightening of the talent market, are hiring the square to fit in the square. It’s exact fit to the job that they’re hiring for as opposed to hiring for potential. And I am going to give an example of this. Back in the day, in the advent of, you know, the early two thousands when we had all of the online startups, uh, I was working for a startup that we were competing with Travelocity and Expedia. And I remember when we were doing our hire and we were hiring for jobs that we didn’t even quite know yet. What would they do? Like what is it?

Michelle Tenzyk (52:18):

I think we know the needs sort of, but not really because the whole world of online and e-commerce and making money was still trying to be figured out. We hired for potential. We did a lot of hiring for potential, which to me was a really smart hiring decision and it all worked out for us today. Companies need to take the risk and higher potential and then provide the learning because right now some of that learning is not expensive, right? There’s plenty of learning platforms that are making it very dynamic and easy for people to get skilled as they’re in that role, if they’ve got the motivation and the desire to do the great work. So I am hopeful that more companies take on that attribute of hiring for potential, especially in a talent shortage because there are people who really want to be working and just may not yet have the skill set. It doesn’t mean they’re not the right fit for you. Because what I hear, even if I go back to enigma, an example, culture, values, environment, still have a strong hold on any company today. It still matters. And so my, the fit of someone to my culture, to my vision and my values is incredibly important for the longterm. And so if you really are demonstrating potential and your ability to want to learn and know more, why wouldn’t I hire you? Even if you don’t have the exact skill set yet for that role.

Terry Tateossian (53:53):

So how do you measure those soft skills? How do you determine that someone is a good fit when it comes to culture, environment and so forth?

Michelle Tenzyk (54:06):

So I haven’t read this yet, but I’m expecting probably when I leave here I’ll read it. AI is going to help with all of that, right? I mean AI right now on the HR front is huge on the recruiting and onboarding. So if you’re able to figure out my fit competency wise on my technical capabilities, you’re also going to be able to feed in data into whatever system it is or application that I’m using to assess your fit. And in fact, I only looked at it briefly, but I’m pretty sure the IBM study was of course Watson at the forefront of that talks about that ability to get the fit right of someone through AI mechanisms and that that should come first as opposed to the rest of my technical skillset coming first. But that ability is in there.

Terry Tateossian (55:11):

Very interesting. So the E Q should come first before the actual IQ test.

Michelle Tenzyk (55:17):

That’s my opinion.

Terry Tateossian (55:18):

Very interesting. I’m really curious on how we’re going to actually measure, you know, resilience, tenacity, ability to not quit, ability to iterate your process. And that brings me to my next point. How do we build algorithms that can assess the skills that don’t even necessarily make exist in person at the time that they’re there?

Michelle Tenzyk (55:44):

Yes. So so here, here’s that, right? Um, and I will make sure I get you this BM paper cause it’s really interesting. So if you think about, if you, if you have a sizable workforce and you start looking at and you start analyzing length of service kind of work that someone has been doing their ability to manage and the ups and downs of the business, now I start pulling out that information out of algorithms, right? Because I start getting the data out, I start looking at the compilation of the workforce. I start to see who was able to sustain during periods of challenge, who left, who actually exited and resigned, right? So who’s no longer there. And then while they were there, what was their behaviors or actions that kept them there? So there they are starting the, I might be behind times already.

Michelle Tenzyk (56:45):

It’s, it’s out there. Is it out there that’s prevalent? Not yet, but is it coming? It sure is that I’m, I will have that ability through AI and analytics to do that. And predictive analytics, take one action immediately after listening to this podcast that will contribute to your learning in and around the world of AI and automation, whatever that might be for you. But take one action. You can do it today. You don’t have to wait. Do it today. Read something, Google something, talk to someone, look into a new app, whatever that might be. But the one action that you can take because as soon as you take an action it feels like it’s possible.

Terry Tateossian (57:28):

So Michelle, how can people find you?

Michelle Tenzyk (57:31):

Sure. So people can find us at and welcome you to come to our website. Check us out, see what we’re up to, see what we’re doing. And you can always email me at Be happy to hear from you or take any of your questions or thoughts. Thank you.

Terry Tateossian (57:53):

Perfect. Well thank you very much for joining us on the amplified podcast. You are a treasure trove of really valuable information. It is very clear that you have a lot of experience working with high level CEOs and executives and guiding and steering them to finding the right solutions that will help them continue on and grow their businesses. So we appreciate you.

Michelle Tenzyk (58:20):

Thank you. Loved being here.

Terry Tateossian (58:22):

Thanks for listening to the amplified podcast. Follow us on our social channels and subscribe on Apple and Google podcasts, Spotify, pod bean, or wherever you get your podcasts on the next episode. Stay tuned for more trailblazing insights, energy, and culture to help fuel your pursuit in the modern digital era. Yeah.


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